LIMSI@CoNLL’17: UD Shared Task

Lauriane Aufrant, Guillaume Wisniewski, François Yvon


Abstract
This paper describes LIMSI’s submission to the CoNLL 2017 UD Shared Task, which is focused on small treebanks, and how to improve low-resourced parsing only by ad hoc combination of multiple views and resources. We present our approach for low-resourced parsing, together with a detailed analysis of the results for each test treebank. We also report extensive analysis experiments on model selection for the PUD treebanks, and on annotation consistency among UD treebanks.
Anthology ID:
K17-3017
Volume:
Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies
Month:
August
Year:
2017
Address:
Vancouver, Canada
Editors:
Jan Hajič, Dan Zeman
Venue:
CoNLL
SIG:
SIGNLL
Publisher:
Association for Computational Linguistics
Note:
Pages:
163–173
Language:
URL:
https://aclanthology.org/K17-3017
DOI:
10.18653/v1/K17-3017
Bibkey:
Cite (ACL):
Lauriane Aufrant, Guillaume Wisniewski, and François Yvon. 2017. LIMSI@CoNLL’17: UD Shared Task. In Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, pages 163–173, Vancouver, Canada. Association for Computational Linguistics.
Cite (Informal):
LIMSI@CoNLL’17: UD Shared Task (Aufrant et al., CoNLL 2017)
Copy Citation:
PDF:
https://aclanthology.org/K17-3017.pdf
Data
Universal Dependencies